Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

The Thoracic Cage: Ribs01:20

The Thoracic Cage: Ribs

10.6K
Ribs are curved, flattened bones forming the thoracic cavity wall with the thoracic muscles. There are 12 pairs of thoracic ribs. The posterior ends of all the ribs articulate with the T1–T12 thoracic vertebrae. In contrast,the anterior ends of most ribs attach to the sternum via their costal cartilages.
Parts of a Typical Rib
A typical rib has a head, neck, and body. The posterior end of the rib is called the head, followed by a narrow neck. The head articulates primarily with the costal...
10.6K
The Thoracic Cage: Sternum01:17

The Thoracic Cage: Sternum

9.7K
The thoracic or rib cage forms the body's thorax (chest) portion. Its primary function in the body is to protect vital organs in the thoracic cavity, such as the heart and the lungs. It consists of 12 pairs of ribs with their costal cartilages and the sternum. The ribs are anchored posteriorly to the 12 thoracic vertebrae (T1-T12).
The sternum is the elongated bony structure on the anterior side of the thoracic cage. It consists of three parts: the manubrium, the body, and the xiphoid...
9.7K
Radiological Investigation I: X-ray and CT01:30

Radiological Investigation I: X-ray and CT

1.5K
Radiological investigations, including X-rays and computed tomography (CT) scans, are critical for diagnosing and evaluating various medical conditions. These imaging techniques provide valuable insights into the body's internal structures, aiding in the detection of abnormalities, assessment of disease progression, and development of treatment strategies. This article delves into two primary radiological investigations, chest X-rays and CT scans, outlining their purpose, procedures, and...
1.5K
X-ray Imaging01:24

X-ray Imaging

11.0K
German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with...
11.0K
Classification of Bones01:18

Classification of Bones

12.2K
The bones of the human skeletal system are of varied shapes, sizes, and functions. They can be classified based on their shape and function into four major classes: long bones, short bones, flat bones, and irregular bones. Some classifications include a fifth type, the sesamoid bones, as a separate class, whereas others categorize them under short bones.
Long and Short Bones
The appendicular skeleton, particularly the upper and lower limbs, is primarily made of long and short bones. The...
12.2K
Overview of the Axial Skeleton01:09

Overview of the Axial Skeleton

13.4K
The skeleton is subdivided into two major divisions—the axial skeleton and the appendicular skeleton. The axial skeleton forms the vertical, central axis of the body. It includes all of the bones of the head, neck, chest, and back. It protects the brain, spinal cord, heart, and lungs. It also serves as the attachment site for muscles that move the head, neck, and back and for muscles that act across the shoulder and hip joints to move their corresponding limbs.
The axial skeleton of the...
13.4K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Considerations for Pre-deployment Planning in Point-of-Care Ultrasound Program Implementation: A HIMSS-SIIM Enterprise Imaging Community Whitepaper in Collaboration with AIUM.

Journal of imaging informatics in medicine·2026
Same author

REN: Anatomically-Informed Mixture-of-Experts for Interstitial Lung Disease Diagnosis.

IEEE transactions on medical imaging·2026
Same author

Multimodal AI for early prediction of adverse clinical outcomes in acute pancreatitis.

Abdominal radiology (New York)·2026
Same author

A Predictive MRI Radiomics Model for Histologic Differentiation in Soft Tissue Sarcomas.

Cancers·2026
Same author

Diverse image generation with diffusion models and cross class label learning for polyp classification.

Scientific reports·2026
Same author

Mitigating hallucinations in synthesized clinical texts to improve multimodal deep learning for dermatology.

Journal of biomedical informatics·2026
Same journal

RGCNN-nnUNet: Recurrent group equivariant nnU-Net for robust brain tissue segmentation on stroke NCCT.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society·2026
Same journal

Self-supervised isotropic reconstruction for abnormality detection in anisotropic MRI.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society·2026
Same journal

WDBDM: Wavelet-based dual-branch diffusion model for low-dose CT and PET denoising.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society·2026
Same journal

ScribSAM: A robust scribble-supervised framework for spatiotemporal segmentation of breast lesions in ultrasound videos.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society·2026
Same journal

Anatomically and biochemically guided deep image prior for sodium MRI denoising.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society·2026
Same journal

Segment Anything Model for medical image segmentation: A review.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society·2026
See all related articles

Related Experiment Video

Updated: Mar 21, 2026

Longitudinal Micro-Computed Tomography Image Analysis for User-Defined Region of Interest in Critical-Sized Bone Defects
08:39

Longitudinal Micro-Computed Tomography Image Analysis for User-Defined Region of Interest in Critical-Sized Bone Defects

Published on: June 24, 2025

704

Atlas-based rib-bone detection in chest X-rays.

Sema Candemir1, Stefan Jaeger1, Sameer Antani1

  • 1Lister Hill National Center for Biomedical Communications U.S. National Library of Medicine, National Institutes of Health, Bethesda, MD, USA.

Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society
|May 9, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces rib-bone atlases for automatic rib detection in chest X-rays (CXRs). The developed system accurately identifies posterior rib borders, improving diagnostic efficiency.

Keywords:
Chest X-raysRib bone extraction

More Related Videos

Pedicle Screw Placement Using an Augmented Reality Head-Mounted Display in a Porcine Model
06:18

Pedicle Screw Placement Using an Augmented Reality Head-Mounted Display in a Porcine Model

Published on: May 24, 2024

2.9K
Automated Joint Space Detection Improves Bone Segmentation Accuracy
06:45

Automated Joint Space Detection Improves Bone Segmentation Accuracy

Published on: November 28, 2025

262

Related Experiment Videos

Last Updated: Mar 21, 2026

Longitudinal Micro-Computed Tomography Image Analysis for User-Defined Region of Interest in Critical-Sized Bone Defects
08:39

Longitudinal Micro-Computed Tomography Image Analysis for User-Defined Region of Interest in Critical-Sized Bone Defects

Published on: June 24, 2025

704
Pedicle Screw Placement Using an Augmented Reality Head-Mounted Display in a Porcine Model
06:18

Pedicle Screw Placement Using an Augmented Reality Head-Mounted Display in a Porcine Model

Published on: May 24, 2024

2.9K
Automated Joint Space Detection Improves Bone Segmentation Accuracy
06:45

Automated Joint Space Detection Improves Bone Segmentation Accuracy

Published on: November 28, 2025

262

Area of Science:

  • Radiology
  • Medical Imaging
  • Computer-Aided Diagnosis

Background:

  • Accurate detection of rib bones in chest X-rays (CXRs) is crucial for diagnosing various thoracic conditions.
  • Existing methods for rib segmentation in CXRs face challenges with anatomical variations and image quality.

Purpose of the Study:

  • To investigate the efficacy of rib-bone atlases for automated posterior rib border detection in CXRs.
  • To develop and evaluate a system utilizing conventional and novel rib-bone atlases for enhanced rib segmentation accuracy.

Main Methods:

  • A system was developed to automatically compute posterior rib borders using patient CXRs and model atlases.
  • Two alternative atlases were proposed: rib bone models from Computed Tomography (CT) scans and dual-energy CXRs.
  • The approach was tested on 50 CXRs from the Japanese Society of Radiological Technology (JSRT) and National Library of Medicine (NLM) datasets.

Main Results:

  • The system achieved high accuracy in detecting posterior rib borders, with an Area Under the ROC Curve (AUC) of approximately 95% for the Montgomery dataset and 91% for the JSRT dataset.
  • Segmentation accuracy reached 88.91±1.8% for the Montgomery dataset and 85.48±3.3% for the JSRT dataset at the optimal operating point.
  • The method demonstrated robustness in handling variations in rib shape and the number of visible ribs due to patient respiration.

Conclusions:

  • Rib-bone atlases provide an effective tool for automatic and accurate detection of posterior rib borders in chest X-rays.
  • The proposed system, incorporating novel CT-derived and dual-energy CXR atlases, offers a robust solution for rib segmentation, comparable to state-of-the-art methods.
  • This automated approach holds promise for improving the efficiency and accuracy of radiological assessments involving rib structures.